namemyapp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; the description carries the behavioral burden. It discloses the API key requirement and the sources checked (trademarks, homepages, search results), but does not specify return format, rate limits, or whether the operation is safe (read-only).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with an additional API key note, all front-loaded with the core purpose. No wasted words, and the structure is clear and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple check tool with no output schema, the description adequately states the input (name) and what it checks, but omits details about the output format (e.g., boolean, list of conflicts) and how the context parameter affects results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema: 'context' is described as 'Optional industry/product context to narrow results' in both places.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Check if a brand name conflicts with USPTO trademarks, live company homepages, or search results,' providing a specific verb and resource. This distinguishes it from sibling tools like check_domain (domain availability) and generate_names (name generation).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. While the description mentions it is free for all tiers and requires an API key, it does not compare to sibling tools or specify when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses return type (success/failure) and requirement for API key and stored payment method. However, with no annotations, it fails to detail side effects (e.g., charges, domain registration) or error conditions beyond success/failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus a bracketed note, all essential. Front-loaded with purpose, no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequately covers the tool's action, return, and prerequisites for a simple 2-parameter tool. Could mention prerequisite of checking domain availability or setting up payment, but acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% coverage with descriptions for both parameters. Description adds no further meaning to parameters beyond what schema provides, achieving baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Purchase a domain using the stored payment method', specifying the verb (purchase), resource (domain), and method (stored payment). Differentiates from siblings like 'check_domain' and 'buy_link' which operate on different resources or actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Does not provide guidance on when to use this tool versus alternatives like 'check_domain' for availability or 'buy_link' for other purchases. Mentions required API key but lacks explicit usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It states the tool generates a URL without requiring an API key, but does not explicitly disclose behavior for invalid domains or potential errors. It implies no side effects, but transparency could be improved with explicit disclaimers.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. The first sentence states purpose, the second gives usage guidance and availability. Highly concise and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity, no output schema, and 2 parameters, the description covers when to use, availability, and return type (implicitly a URL). It is nearly complete, though could explicitly state the return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The tool description does not add extra parameter details beyond what the schema provides (e.g., priceUsd optional). It meets minimum but adds no additional semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds a one-click purchase URL for buying a domain on namemy.app, with the verb 'build' and resource 'purchase URL'. It also distinguishes itself from the sibling tool 'check_domain_public' by focusing on purchase after name selection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this when the user has decided on a name they like' and mentions it works without an API key, providing clear context for when to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided; the description does not disclose behavioral traits such as whether pricing is real-time, if there are rate limits, or what happens if the domain is unavailable. The phrase 'cheapest registrar' implies aggregation but lacks detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, with no extraneous words. Every sentence adds value, including the API key requirement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description covers the basic purpose and a key prerequisite. However, it lacks details on return format or error handling, leaving some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a good example in the schema description. The description does not add further meaning beyond what the schema provides, so baseline score applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool checks domain availability and obtains pricing from the cheapest registrar. However, it does not differentiate from sibling tool 'check_domain_public', leaving ambiguity about when to use which.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions a required API key with a link, which is helpful, but it provides no guidance on when to use this tool versus alternatives like 'check_domain_public' or other domain-related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses rate-limiting and no API key requirement, and that it returns availability and indicative pricing. Lacks specifics of rate limit but adequate for a simple tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded with action, no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no annotations or output schema, the description covers purpose, usage, limitations, alternatives, and return types completely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear description of the 'domain' parameter. Description adds no extra meaning beyond the schema, so baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'Check', resource 'domain', and unique aspect 'without requiring an API key'. Distinguishes from siblings by highlighting the free, rate-limited nature.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (no API key) and when not (for full pricing/registration, use check_domain or buy_domain). Provides clear alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key behaviors: public, no auth, returns array with specific fields (availability, price, renewal, registrar, buyUrl). It mentions performance benefits but lacks details on error handling or rate-limiting implications. Still, it's fairly transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is three concise sentences with no redundancy. First sentence covers public/no-key and bulk advantage; second explains return fields; third gives usage preference. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple bulk domain check tool with one parameter and no output schema, the description covers purpose, usage guidelines, return format, and preference advice. It is complete and leaves no obvious gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds an example format for the 'domains' parameter, clarifying it expects fully-qualified domains. This adds value beyond the schema definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'check', resource 'domains public' in bulk, and explicitly distinguishes from sibling 'check_domain_public' by noting it checks up to 50 domains in one call, being faster and reducing rate-limit hits.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to prefer this tool over multiple check_domain_public calls when having more than one candidate, providing clear when-to-use guidance. Also notes it requires no API key.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses generation behavior and requirements (subscription, API key), but does not mention side effects, idempotency, rate limits, or return format. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: first states purpose with components, second states requirements. No fluff, front-loaded with key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite complexity (4 params, no output schema), description lacks parameter explanations, return value details, and usage examples. Covers requirements but not what to expect from output or how parameters affect results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and description provides no explanation of parameters (name, industry, description, includeVisuals). Only 'name' is implied as the brand name, but other fields are undocumented. This is a significant gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it generates a complete brand kit with a list of components (essentials, audience, personality, etc.), distinguishing it from sibling tools like generate_logo or generate_social_kit which focus on specific outputs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description specifies prerequisites (Founder sub or BRAND_KIT purchase, API key) but does not explicitly clarify when to use this tool versus alternatives. However, the requirements imply it's for generating a full brand identity, which provides some guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions prerequisites but does not disclose behavioral traits such as what the tool returns, whether it mutates data, rate limits, or error states. This is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise—two sentences front-load the core purpose and prerequisites with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, no output schema, and no annotations, the description is incomplete. It omits return format, error handling, region-specific behavior details, and any post-invocation context an agent would need.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (20%), and the description adds little parameter meaning beyond names. It does not explain regions (despite a default), websiteUrl, businessName, or contactEmail. Only businessType is partially described in the schema via an enum hint.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates specific legal documents (Privacy Policy, Terms of Service, Cookie Policy) and is region-aware (GDPR, CCPA, LGPD). This distinguishes it from sibling tools like generate_brand_kit or generate_logo.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions requirements (Founder sub or LEGAL_KIT purchase, free API key) but does not explicitly state when not to use or provide alternatives. The context is clear but lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses prerequisites (subscription, API key) and that it returns N variations. However, it omits behavioral traits like rate limits, whether the operation is destructive, or return format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus a note in brackets, all front-loaded with essential info. There is no redundancy or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters including a nested object and no output schema, the description is insufficient. It does not explain the return value format, how preferences affect output, or how this differs from generate_brand_kit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only 40% of parameters have schema descriptions (count and description). The tool description adds no additional meaning to the parameters; it does not explain 'name', 'slogan', or the nested 'preferences' object beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates AI logo concepts including specific elements (icon, palette, typography, layout) for a business, and mentions it returns N variations. This is a specific verb+resource that distinguishes it from sibling tools like generate_brand_kit or check_domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides prerequisites (subscription or purchase, API key) but does not explicitly guide when to use this tool versus alternatives like generate_brand_kit. There is no when-not or comparison with siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Given no annotations, the description partially conveys behavior (real-time checks, API key required) but omits details like side effects, rate limits, or caching.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two effective sentences: the first states the core function, the second adds the key behavioral claim and prerequisite. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the description hints at the return (names with availability and pricing). Could specify structure but sufficient for basic understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All parameters are described in the input schema (100% coverage), so the description adds limited parameter-specific meaning beyond stating 'real-time' and 'pricing'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates brandable business names, with the specific value-add of real-time domain availability. This distinguishes it from sibling tools like check_domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly mentions the prerequisite API key and where to obtain it, but lacks guidance on when to use this tool versus alternatives like brand_conflict_check.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses the requirement for a subscription/purchase and an API key, which are important behavioral constraints. However, it doesn't describe what happens if requirements aren't met (e.g., error), rate limits, or any side effects. This is adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first defines the core function, the second lists prerequisites. Every word is necessary; there is no redundancy or fluff. The structure is front-loaded with the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (generating a social media kit), no output schema, and 7 parameters with no description coverage, the description is incomplete. It fails to explain the output format, how parameters influence the result, or any usage nuances. The prerequisites are noted, but that alone is insufficient for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the description adds no detail about parameters like businessName, industry, goals, etc. The schema itself provides minimal hints (e.g., enums for voiceTone), but the description should compensate and fails to do so. An agent would need to infer parameter meanings from the tool's overall purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it generates a social media strategy and content kit, listing specific deliverables (posts, captions, calendar, analytics framework). This verb+resource combination is distinct from sibling tools like generate_brand_kit or generate_logo.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly mentions prerequisites: 'Requires Founder sub or SOCIAL_MEDIA_KIT purchase' and 'Requires a free namemy.app API key'. This tells the agent when to use the tool (if requirements met) and by omission when not to. However, it does not compare with alternatives or state when another tool is preferable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It mentions the requirement for a free API key, which is helpful, but does not disclose other aspects like rate limits, pagination, or whether it lists active or all domains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: one for purpose, one for a key prerequisite. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and no output schema, the description covers the functionality and a necessary prerequisite. It is sufficient for an agent to understand the basic operation, though it lacks details about return format or filtering.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters in the input schema, so baseline is 4. The description does not add parameter meaning but includes a relevant prerequisite about API keys.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it lists all domains owned by the user. This is a specific verb ('list') and resource ('domains'), and it distinguishes from sibling tools that check, buy, or generate domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide guidance on when to use this tool versus its siblings, such as to list domains vs. check availability or buy. The only guideline is a prerequisite about API keys.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It indicates a write operation ('Add or update') and mentions an API key requirement. However, it does not disclose whether records are upserted, rate limits, or permissions beyond the API key. Adequate but not detailed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief (one sentence plus a note in brackets) and front-loaded with purpose. It is concise with no unnecessary words, though slightly informal with square brackets for the API key note.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter mutation tool with no output schema, the description covers purpose and common uses but lacks details on return values, error handling, TTL behavior, or confirmation. It is reasonably complete given sibling domain tools don't overlap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (only 'host' parameter has description). The description text does not explain any parameter meanings, defaults, or constraints beyond what the schema provides. Given the low coverage, the description should have compensated but did not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Add or update a DNS record for a domain') and lists specific use cases (pointing to Vercel, Netlify, email services). No sibling tool overlaps with DNS management, so differentiation is inherent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for when to use the tool ('pointing domains to Vercel, Netlify, or email services'), but lacks explicit guidance on when not to use it or alternative tools. Given no sibling overlaps, this is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.